Cooperative Spectrum Sensing with Amplify and Forward Scheme in CRNs

Author:

Sharma Krishnakant,Awasthi Meenakshi

Abstract

AbstractRecent research has identified cognitive radio (CR) as a possible solution for increasing spectrum usage by allowing secondary access to unlicensed bands. Having no interference with the primary system is a need for this secondary access. Due to this requirement, spectrum sensing becomes a crucial component of cognitive radio systems. The ease and effectiveness of energy detection make it an appealing technique among popular spectrum sensing techniques. The uses of the available radio network spectrum, finite and important resources, have been severely constrained by the rising demand for wireless applications. It is essential to develop a successful cooperative spectrum sensing (CSS) system for cognitive radio (CR), whose are seen to be a promising solution for improving spectrum usage. A clusters-based optimal selective CSS system is suggested in this paper to shorten reporting times for the bandwidth whiles preserving a given performance by the sensing mode. The clusters have a dynamic head in each selected cluster in accordance with data sensing qualities for CR users in the cognitive radio. Clusters have been arranged based on identifying the major signals to the noise ratio value. Making a decision to use cluster sensing is based on a chosen CSS threshold that minimizes the likelihood of sensing inaccuracy. It takes less time to make the report for the decision of the clusters’ fusion centre is significantly reduced by the Amplify and Forward-based CSS approach that is proposed. The optimal Chair-Varshney rule is applied to the fusion centre for achieving a high sensing performance is depending on the information that is currently available about the cluster. Based on the results availability of simulation, it is clear to propose a way to supersede the other existing methods.

Publisher

IOP Publishing

Subject

Computer Science Applications,History,Education

Reference46 articles.

1. Energy-Efficient Distributed Spectrum Sensing for Cognitive Sensor Networks;Maleki;IEEE Sensors Journal,2011

2. CORVUS: A cognitive radio approach for usage of virtual unlicensed spectrum;Broderson,2004

3. Spectrum policy task force report;Federal Communications Commission,2002

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3